Research on online energy consumption metering methods for variable refrigerant flow air conditioning systems

Real-time operation energy consumption is the basic data of the energy-saving operation and online smart control for variable refrigerant flow (VRF) systems. However, power meter is rarely installed on VRF systems for energy consumption monitoring in real projects due to their high cost. As a result, research on economy and accurate real-time energy consumption measuring method for VRF systems is of great significance for energy saving and carbon reduction. In this paper, a frequency-current surface fitting method in single chip microcomputer cases and a neural network self-learning method in cloud big data cases are proposed. Experimental results illustrate that both two methods show high measurement accuracy. The measurement errors of the total power of the VRF system distribute within ±5% in various operating conditions including nominal cooling, nominal heating, maximum cooling, low temperature heating, defrosting and 45 h free switching operating conditions.